Ya. N. Gladchenko-Djevelekis, D. B. Tolchina, V. V. Srabionyan, V. A. Durymanov, L. A. Avakyan, L. A. Bugaev
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引用次数: 0
摘要
摘要 众所周知,基于双金属铂铜纳米粒子的材料的催化性能取决于这些粒子中原子的组成和分布。因此,要开发出具有更好催化性能的新材料,就必须采用准确可靠的实验方法来确定纳米粒子(NPs)的结构(随机固溶体、Janus、核壳或 "梯度")。我们之前的研究通过机器学习模拟证明,利用精确的理论计算配对原子径向分布函数(RDFs)可以确定单个双金属纳米粒子的结构,而这些信息也可以从最常见的 NP 结构信息来源(如 X 射线吸收光谱(XAS)和 X 射线衍射(XRD)技术)中获得。这项工作是上述研究的逻辑延续,致力于从理论上研究确定 RDFs 时的误差影响,以及纳米粒子的尺寸和成分分布对从其 RDFs 确定纳米粒子结构的可能性的影响。
Machine Learning for Determining the Architecture of Ensembles of Bimetallic PtCu Nanoparticles Based on Atomic Radial Distribution Functions
It is known that the catalytic properties of materials based on bimetallic PtCu nanoparticles depend on both the composition and the distribution of atoms in these particles. Therefore, the development of new materials with improved catalytic properties requires the application of an accurate and reliable experimental method for determining the architecture of nanoparticles (NPs) (random solid solution, Janus, core–shell or “gradient”). Our previous study demonstrated through machine-learning simulations that the architecture of single bimetallic nanoparticles can be determined using accurate theoretically calculated paired atomic radial distribution functions (RDFs), which can also be obtained from the most common sources of NP structural information, such as the X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD) techniques. This work is a logical continuation of the research mentioned above and is devoted to a theoretical study of the influence of errors in determining the RDFs, as well as the influence of the size and composition distributions of nanoparticles on the possibility of determining the architecture of nanoparticles from their RDFs.
期刊介绍:
Nanobiotechnology Reports publishes interdisciplinary research articles on fundamental aspects of the structure and properties of nanoscale objects and nanomaterials, polymeric and bioorganic molecules, and supramolecular and biohybrid complexes, as well as articles that discuss technologies for their preparation and processing, and practical implementation of products, devices, and nature-like systems based on them. The journal publishes original articles and reviews that meet the highest scientific quality standards in the following areas of science and technology studies: self-organizing structures and nanoassemblies; nanostructures, including nanotubes; functional and structural nanomaterials; polymeric, bioorganic, and hybrid nanomaterials; devices and products based on nanomaterials and nanotechnology; nanobiology and genetics, and omics technologies; nanobiomedicine and nanopharmaceutics; nanoelectronics and neuromorphic computing systems; neurocognitive systems and technologies; nanophotonics; natural science methods in a study of cultural heritage items; metrology, standardization, and monitoring in nanotechnology.